Individualized treatment based on ovarian reserve markers

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Julie Craig
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1 Individualized treatment based on ovarian reserve markers Prof Dr. Nikolaos P. Polyzos M.D. PhD Professor and Medical Co- Director, Vrije Universiteit Brussel, UZ Brussel, Belgium Professor of Reproduc?ve Endocrinology University of Aarhus Denmark

2 What is more fascinating than. Prediction

3 Ovarian reserve markers Ø Reflect the number of non-growing follicles in the female ovary Ø Can predict the level of ovarian response after ovarian stimulation

4 Which is the ideal ovarian reserve marker? q Can predict excessive and poor response to stimulation q Reliable q Stable (can be measured anytime we want)

5 Ovarian reserve tests and response prediction Excessive response Low response Broer et al. Fertil Steril 2013 Broer et al. Hum. Reprod. Update 2013

6 Reliability Antral follicle count (AFC) LIMITATIONS AFC may have variability when different or inexperienced sonographers perform the scan It is better to be measured on day 2-3 of the menstrual cycle

7 Stability AMH is a stable marker across 4 consecutive cycles Stability is higher compared to AFC van Disseldorp Hum Reprod 2010

8 Stability Hehenkamp JCEM 2006 La Marca Hum Reprod 2006 AMH can be measured any day of the menstrual cycle

9 Can ovarian reserve markers predict pregnancy? Broer et al. Hum. Reprod. Update 2013 Brondin et al., JCEM 2013

10 Why do we need to individualize treatment if we can t predict pregnancy?

11 Importance of personalized treatment Sunkara et al., Hum Reprod 2011 La Marca &Sunkara Hum Reprod 2013

12 icos ( individualized controlled ovarian stimulation) One size does not fit all Based on ovarian reserve markers we can select the 1. Type of analogue 2. The dose of gonadotropins Ovarian stimulation can be Patient friendly Safe Effective Cost-effective Is this really true?

13 AMH guided ovarian stimulation (1) AMH group (pmol/l) Centre 1 Centre 2 <1.0 Antagonist-375IU Modified natural cycle 1.0 to <5 Agonist-375IU Antagonist-300IU 5.0 to <15 Agonist-225IU Agonist-225IU 15.0 Agonist-150IU Antagonist-150IU Nelson et al., Hum Reprod 2009

14 AMH guided ovarian stimulation (2) Centre 1 Centre 2 Pvalue Protocol Antagonist IU Agonist IU Number of oocytes collected 10 ( ) 14 (10 19) <0.001 SAFE Freeze all n (%) 0 (0%) 27 (18.2%) Hospitalized for OHSS 0 (0%) 20 (13.9%) Cancelled cycle n (%) 1 (2.9%) 4 (2.7%) 1.0 EFFECTIVE Clinical pregnancy per cycle n (%) 21 (61.7%) 47 (31.8%) High (AMH>15pmol/l) Nelson et al., Hum Reprod 2009

15 AMH guided ovarian stimulation (3) Conventional AMH-tailored Clinical outcomes protocol (n = 346) protocol (n = 423) Adjusted P-value b Number (SD) of oocytes 12.4 ± ± c OHSS leading to Cycle cancellation and/or freeze all 24 (6.9%) 10 (2.3%) Hospital admission 10 (2.9%) 5 (1.2%) 0.15 Live births per cycle started 55 (15.9%) 101 (23.9%) Average cost/ patient/cycle SAFE EFFECTIVE COST- EFFECTIVE Yates et al., Hum Reprod 2011

16 AMH-guided stimulation The ESTHER trial Evidence-based Stimulation Trial With Human rfsh in Europe and Rest of World ~1400 women are randomized New human rfsh with individualized dosing based on AMH values VS Fixed dose 150IU Follitropin beta

17 AFC-guided stimulation The CONSORT trial Olivennes RBMonline 2015

18 AFC-guided stimulation The OPTIMIST trial

19 AFC AMH

20 Comparison of AMH and AFC personalized treatment AMH values (ng/ml) AFC values FSH starting dose <0.7 < >2.1 > Lan et al., RBMonline 2013

21 Comparison of AMH and AFC personalized treatment AMH AFC P-value Hyper-response 15 (8.7) 30 (17.4) 0.02 Cycles cancelled 4 (2.3) 3 (1.7) NS Duration of stimulation 11.8 ± ± 1.3 NS FSH dose Total (IU) 2694 ± ± 1188 NS Daily (IU/day) 224 ± ± Oocytes retrieved 10.8 ± ± 7.3 <0.01 Embryos 6.3 ± ± 4.7 <0.01 Frozen embryos 1.7 ± ± 3.3 <0.01 Beta-HCG positive/et 72 (45.6) 80 (55.2) NS Clinical pregnancy/et 60 (38.0) 68 (46.9) NS Lan et al., RBMonline 2013

22 How should we individualize treatment? Agonist Antagonist Long Short flare up rfsh rlh hphmg

23 The ideal protocol for personalized treatment La Marca &Sunkara Hum Reprod 2013 ( modified from Nelson 2009 and Yates 2011)

24 The ideal protocol for personalized treatment La Marca &Sunkara Hum Reprod 2013

25 When do ovarian reserve tests fall in the 2 nd place? Previous failed attempt

26 Current ovarian response categorization Poor responders How Normal normal responders is the normal responder? High responders <4 oocytes 4-15 oocytes >15 oocytes Is it the same to obtain 4, 5, 6 oocytes with retrieving 12,13 or 14 oocytes

27 The suboptimal responders: An overlooked ovarian response group (1) Definition 4-9 oocytes retrieved after conventional stimulation Who are these patients? Reduced sensitivity to gonadotropins (e.g. FSH or LH receptor mutations) Why do they not respond according to their ovarian reserve? Ovarian reserve markers predict the number of follicles and NOT their sensitivity to gonadotropins Aim in this group Increase number of oocytes retrieved to oocytes Polyzos & Sunkara Hum Reprod 2015

The suboptimal responders: Why should they be identified? They are a lot! 43.3% of all IVF cycles (174.000/ 402.

28 The suboptimal responders: Why should they be identified? They are a lot! 43.3% of all IVF cycles ( / IVF cycles UK HFEA) It may be easy to improve the outcome By using different more potent gonadotropins or higher doses An increase in oocyte yield can substantially improve pregnancy rates Increase ~20-30% in the pregnancy rates in fresh IVF cycles Sunkara et al. Hum Reprod Jul;26(7): Increase in cumulative pregnancy rates from fresh and frozen embryos

29 Cumulative live birth rates according to ovarian response q 1099 women undergoing their 1 st stimulation for IVF/ICSI q IU rfsh and eset 1-3 oocytes n= oocytes n=471 Ovarian response groups oocytes n=327 >15oocytes n=218 P- value Age 32.8 (3.9) 31.6(4.1) 30.5(3.8) 30.3(3.5) <0.001 a Moderate-severe OHSS 0 0 Live birth in the fresh 14 cycle a* (16.87%) Cumulative live birth a* 18 (21.69%) 140 (29.72%) 187 (39.70%) 2 (0.6%) 111 (33.94 %) 165 (50.46 %) 9 (4.1%) 70 (32.11%) 134 (61.47%) <0.001 c 0.02 b <0.001 b

30 Conclusions q Ovarian reserve markers are ideal for predicting oocyte quantity but not quality q Individualized treatment based on AMH and AFC may result in a safer and more effective ovarian stimulation q However ovarian reserve markers cannot predict pregnancy outcome

31 Conclusions q Ovarian response in a previous IVF cycle can guide management for future attempts q Ovarian response categories may need to be revisited q Suboptimal responders may be a new response category which we need to focus in the future

Poor & Hyper responders: what is the best approach?

Poor & Hyper responders: what is the best approach? A. La Marca ObGyn Dept University of Modena and Reggio Emilia Italy Center for Reproductive Medicine University Hospital of Modena Italy Criteria used